2022
Sélection de variables en régression SIR par seuillage doux/dur de la matrice d'intérêt.
An interesting feature of Sliced Inverse Rregression (SIR) is that it allows the construction of indices, as linear combinations of the …
Koh-Lanta, missing data imputation in supervised context
The imputation is the process that estimates the missing values. Simplest approaches impute to fixed values such as mean/median based …
Imputation for supervised learning problems in high dimension
The problem of missing data often occurs in data analysis. Missing values of the type MAR (Missing At Random) are cosidered here. Then, …
Detection of atypical individuals in SIR regression
How can we deal with atypical observations in SIR regression. This can be generalized to any predictive model.
2021
How to deal with missing values in the high dimensional supervised context?
A reflexion about missing data imputation in the supervised context, with a solution and simulation results.
Multiblock supervised analyses. Should we really normalize blocks?
In recent years, data analysis methods have had to deal with new type of heterogeneous data sets. Multi-omics studies are perfect …
Détection d’individus atypiques en régression SIR.
Sliced inverse regression (SIR) focuses on the relationship between a dependent variable $y$ and a $p$-dimensional explanatory variable …
2019
High-dimensional multi-block analysis of factors associated with thrombin generation potential
The identification of novel biological factors associated with thrombin generation, a key biomarker of the coagulation process, remains …
Apprentissage supervisé pour données massives multi-blocs incomplètes
Les récentes innovations techniques ont permis la production de données massives en biologie, comme les données omiques par exemple …
2018
A mono/multi-block sparse PLS for heterogeneous data with missing samples
This is the last update of the current project on dealing with missing samples in multi-block context for supervised datasets.
Une PLS multivoie parcimonieuse avec observations manquantes pour données hétérogènes
Several sets of variables can be analyzed simultaneously by canonical correlation in a multi-way analysis. These sets …
Multiway high-dimensional lasso-penalized analysis with imputation of missing data applied to postgenomic data in an Ebola vaccine trial
Several sets of variables can be analyzed simultaneously by canonical correlation in a multi-way analysis. These sets …
2016
Viral Replicative Capacity Displays a Non-Linear Association to Cytokine Profiles Observed in Acutely Infected Volunteers in Contrast to Viral Load and CD4 T-cell Counts
Using the Meso Scale Discovery (MSD) V-PLEX 40 biomarker cytokine multiplex kit, the cytokine profiles of 108 HIV+ Zambian volunteers …
